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June 28, 2020 08:11
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package main | |
import ( | |
"fmt" | |
"image/color" | |
"log" | |
"math" | |
"sort" | |
"golang.org/x/exp/rand" | |
"gonum.org/v1/gonum/stat" | |
"gonum.org/v1/gonum/stat/distuv" | |
"gonum.org/v1/plot" | |
"gonum.org/v1/plot/plotter" | |
"gonum.org/v1/plot/vg" | |
) | |
const mu float64 = 0.2 | |
const sigma float64 = 0.1 | |
func main() { | |
drawBetaDistributionFunction() | |
drawRandomHistogram() | |
} | |
func drawBetaDistributionFunction() { | |
p, err := plot.New() | |
if err != nil { | |
panic(err) | |
} | |
p.Title.Text = "Beta distribution function" | |
alpha := calcAlpha() | |
beta := calcBeta(alpha) | |
betaDistr := plotter.NewFunction(distuv.Beta{Alpha: alpha, Beta: beta}.Prob) | |
p.Add(betaDistr) | |
p.X.Min = 0 | |
p.X.Max = 1 | |
p.Y.Min = 0 | |
p.Y.Max = 5 | |
if err := p.Save(10*vg.Inch, 10*vg.Inch, "func.png"); err != nil { | |
panic(err) | |
} | |
} | |
func drawRandomHistogram() { | |
p, err := plot.New() | |
if err != nil { | |
panic(err) | |
} | |
p.Title.Text = "Beta distribution and random sample histogram" | |
alpha := calcAlpha() | |
beta := calcBeta(alpha) | |
src := rand.New(rand.NewSource(1)) | |
b := distuv.Beta{Alpha: alpha, Beta: beta, Src: src} | |
v := make(plotter.Values, 10000) | |
sum := 0.0 | |
for i := range v { | |
r := b.Rand() | |
v[i] = r | |
sum = sum + r | |
} | |
sort.Float64s(v) | |
h, err := plotter.NewHist(v, 16) | |
if err != nil { | |
panic(err) | |
} | |
h.Normalize(1) | |
p.Add(h) | |
labels, err := plotter.NewLabels(plotter.XYLabels{ | |
XYs: []plotter.XY{ | |
{X: 0.8, Y: 4.5}, | |
{X: 0.8, Y: 4.3}, | |
{X: 0.8, Y: 4.1}, | |
{X: 0.8, Y: 3.9}, | |
{X: 0.8, Y: 3.7}, | |
{X: 0.8, Y: 3.5}, | |
}, | |
Labels: []string{fmt.Sprintf("Sampled Mean: %f\n", sum/10000.0), fmt.Sprintf("True mean: %f\n", b.Mean()), fmt.Sprintf("Sampled Variance: %f\n", stat.Variance(v, nil)), | |
fmt.Sprintf("True variance: %f\n", b.Variance()), fmt.Sprintf("Sampled Quantile: %f\n", stat.Quantile(0.95, stat.Empirical, v, nil)), | |
fmt.Sprintf("True quantile: %f\n", b.Quantile(0.95))}, | |
}, | |
) | |
if err != nil { | |
log.Fatalf("could not creates labels plotter: %+v", err) | |
} | |
p.Add(labels) | |
betaDistr := plotter.NewFunction(distuv.Beta{Alpha: alpha, Beta: beta}.Prob) | |
betaDistr.Color = color.RGBA{R: 255, G: 100, A: 255} | |
betaDistr.Width = vg.Points(3) | |
p.Add(betaDistr) | |
p.X.Min = 0 | |
p.X.Max = 1 | |
p.Y.Min = 0 | |
p.Y.Max = 5 | |
if err := p.Save(10*vg.Inch, 10*vg.Inch, "hist.png"); err != nil { | |
panic(err) | |
} | |
} | |
func calcAlpha() float64 { | |
return mu * (((mu * (1 - mu)) / math.Pow(sigma, 2)) - 1) | |
} | |
func calcBeta(alpha float64) float64 { | |
return alpha * (1 - mu) / mu | |
} |
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